1. Field of the Invention
The present invention relates to an information processing apparatus and the like that process, for example, information relating to motion of objects, in particular, motion of humans while playing sports and the like.
2. Description of Related Art
As an example of a tool for acquiring motion of objects as digitized data, a tool that measures the position and motion of objects is known (e.g., see JP2001-518185A (e.g., page 1 and FIG. 1)).
Using such a tool allows time-series motion of objects, such as that of humans and animals, to be displayed in waveform graphs and the like. This makes it possible to analyze the motion of a human body, and it seems that from the results of that analysis, it is possible to predict, for example, the parts of the human body that are susceptible to problems.
In the case of analyzing such motion information of humans or animals, it is essential to make comparisons between data sets, or to determine the average of multiple pieces of information. In this case, it is necessary that the multiple pieces of the information can be arranged in alignment in a time axis direction, without disturbing their original waveforms.
However, there has not been established any apparatus or method for arranging multiple pieces of such information in alignment. Therefore, in the case of analyzing motion information of humans or animals, multiple pieces of the information are aligned, for example, by analysts based on their experiences or intuitions. Consequently, the resulting information lacks objectivity, leading to the problem that the reliability of the information is reduced and the information has poor reproducibility. Particularly, in the case of analyzing information of complex motions, the positional relationship between pieces of information will vary depending on, for example, what particular movement included in the complex motion is given attention in order to align pieces of the information, so that many factors need to be considered in performing the alignment, making it difficult to align the information objectively.
For example, let us consider a case where the same motion is performed twice, then a waveform representing motion is acquired from each of the motions, and the waveforms are aligned with each other. At this time, if the time between the start and the end greatly differs between the two motions, then it is conceivable, for example, that when the start time of the motions are aligned, the positional shift between the waveforms increases as the end of the motions approaches. Furthermore, even if particular peaks of the waveforms are aligned with each other, it is conceivable, for example, that the positional shift between the waveforms increases at other parts. As such, it has been difficult to objectively align waveforms, while giving consideration to the balance between the waveforms as a whole.
It is also conceivable to match the start time and the end time between two motion waveforms by changing one of the motion waveforms, thereby aligning the waveforms. However, the details of, for example, the timing or form of motion and the like of humans vary depending on, for example, the duration of the entire motion. For example, the form of a human while running slowly and the form of a human while running fast are completely different. Therefore, even if the duration of a waveform representing motion obtained from the form when running slowly is changed in accordance with the duration of a waveform representing motion in running fast, the resulting waveform will be completely different from the waveform representing motion when running fast. For this reason, performing alignment by changing the waveform in this manner is not appropriate for alignment of waveforms representing motion, especially in the case of analyzing motion, for example.